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  • Research Article
  • Open Access

Real-Time Recognition of Percussive Sounds by a Model-Based Method

  • Umut Şimşekli1,
  • Antti Jylhä2Email author,
  • Cumhur Erkut2 and
  • A. Taylan Cemgil1
EURASIP Journal on Advances in Signal Processing20102011:291860

Received: 22 September 2010

Accepted: 26 November 2010

Published: 6 December 2010


Interactive musical systems require real-time, low-latency, accurate, and reliable event detection and classification algorithms. In this paper, we introduce a model-based algorithm for detection of percussive events and test the algorithm on the detection and classification of different percussive sounds. We focus on tuning the algorithm for a good compromise between temporal precision, classification accuracy and low latency. The model is trained offline on different percussive sounds using the expectation maximization approach for learning spectral templates for each sound and is able to run online to detect and classify sounds from audio stream input by a Hidden Markov Model. Our results indicate that the approach is promising and applicable in design and development of interactive musical systems.


Markov ModelClassification AccuracyHide Markov ModelExpectation MaximizationEvent Detection

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Authors’ Affiliations

Department of Computer Engineering, Boğaziçi University, İstanbul, Turkey
Department of Signal Processing and Acoustics, Aalto University School of Science and Technology, Aalto, Finland


© Umut Şimşekli et al. 2011

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.